Datasets:

QNN
/

autotrain-data-auto2

Tasks:

Token Classification

Languages:

English

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autotrain-data-auto2 / README.md

autotrain-data-processor

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	---
	language:
	- en
	task_categories:
	- token-classification

	---
	# AutoTrain Dataset for project: auto2

	## Dataset Description

	This dataset has been automatically processed by AutoTrain for project auto2.

	### Languages

	The BCP-47 code for the dataset's language is en.

	## Dataset Structure

	### Data Instances

	A sample from this dataset looks as follows:

	```json
	[
	{
	"tokens": [
	"Pd",
	"has",
	"been",
	"regarded",
	"as",
	"one",
	"of",
	"the",
	"alternatives",
	"to",
	"Pt",
	"as",
	"a",
	"promising",
	"hydrogen",
	"evolution",
	"reaction",
	"(HER)",
	"catalyst.",
	"Strategies",
	"including",
	"Pd-metal",
	"alloys",
	"(Pd-M)",
	"and",
	"Pd",
	"hydrides",
	"(PdH<sub><i>x</i></sub>)",
	"have",
	"been",
	"proposed",
	"to",
	"boost",
	"HER",
	"performances.",
	"However,",
	"the",
	"stability",
	"issues,",
	"e.g.,",
	"the",
	"dissolution",
	"in",
	"Pd-M",
	"and",
	"the",
	"hydrogen",
	"releasing",
	"in",
	"PdH<sub><i>x</i></sub>,",
	"restrict",
	"the",
	"industrial",
	"application",
	"of",
	"Pd-based",
	"HER",
	"catalysts.",
	"We",
	"here",
	"design",
	"and",
	"synthesize",
	"a",
	"stable",
	"Pd-Cu",
	"hydride",
	"(",
	"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
	")",
	"catalyst,",
	"combining",
	"the",
	"advantages",
	"of",
	"both",
	"Pd-M",
	"and",
	"PdH<sub><i>x</i></sub>",
	"structures",
	"and",
	"improving",
	"the",
	"HER",
	"durability",
	"simultaneously.",
	"The",
	"hydrogen",
	"intercalation",
	"is",
	"realized",
	"under",
	"atmospheric",
	"pressure",
	"(1.0",
	"atm)",
	"following",
	"our",
	"synthetic",
	"approach",
	"that",
	"imparts",
	"high",
	"stability",
	"to",
	"the",
	"Pd-Cu",
	"hydride",
	"structure.",
	"The",
	"obtained",
	"PdCu<sub>0.2</sub>H<sub>0.43</sub>",
	"catalyst",
	"exhibits",
	"a",
	"small",
	"overpotential",
	"of",
	"28",
	"mV",
	"at",
	"10",
	"mA/cm<sup>2</sup>",
	",",
	"a",
	"low",
	"Tafel",
	"slope",
	"of",
	"23",
	"mV/dec",
	",",
	"and",
	"excellent",
	"HER",
	"durability",
	"due",
	"to",
	"its",
	"appropriate",
	"hydrogen",
	"adsorption",
	"free",
	"energy",
	"and",
	"alleviated",
	"metal",
	"dissolution",
	"rate.",
	"</p>",
	"<p>"
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	},
	{
	"tokens": [
	"A",
	"critical",
	"challenge",
	"in",
	"energy",
	"research",
	"is",
	"the",
	"development",
	"of",
	"earth",
	"abundant",
	"and",
	"cost-effective",
	"materials",
	"that",
	"catalyze",
	"the",
	"electrochemical",
	"splitting",
	"of",
	"water",
	"into",
	"hydrogen",
	"and",
	"oxygen",
	"at",
	"high",
	"rates",
	"and",
	"low",
	"overpotentials.",
	"Key",
	"to",
	"addressing",
	"this",
	"issue",
	"lies",
	"not",
	"only",
	"in",
	"the",
	"synthesis",
	"of",
	"new",
	"materials,",
	"but",
	"also",
	"in",
	"the",
	"elucidation",
	"of",
	"their",
	"active",
	"sites,",
	"their",
	"structure",
	"under",
	"operating",
	"conditions",
	"and",
	"ultimately,",
	"extraction",
	"of",
	"the",
	"structure-function",
	"relationships",
	"used",
	"to",
	"spearhead",
	"the",
	"next",
	"generation",
	"of",
	"catalyst",
	"development.",
	"In",
	"this",
	"work,",
	"we",
	"present",
	"a",
	"complete",
	"cycle",
	"of",
	"synthesis,",
	"operando",
	"characterization,",
	"and",
	"redesign",
	"of",
	"an",
	"amorphous",
	"cobalt",
	"phosphide",
	"(",
	"CoP",
	"<sub><i>x</i></sub>",
	")",
	"bifunctional",
	"catalyst.",
	"The",
	"research",
	"was",
	"driven",
	"by",
	"integrated",
	"electrochemical",
	"analysis,",
	"Raman",
	"spectroscopy",
	"and",
	"gravimetric",
	"measurements",
	"utilizing",
	"a",
	"novel",
	"quartz",
	"crystal",
	"microbalance",
	"spectroelectrochemical",
	"cell",
	"to",
	"uncover",
	"the",
	"catalytically",
	"active",
	"species",
	"of",
	"amorphous",
	"CoP",
	"<sub><i>x</i></sub>",
	"and",
	"subsequently",
	"modify",
	"the",
	"material",
	"to",
	"enhance",
	"the",
	"activity",
	"of",
	"the",
	"elucidated",
	"catalytic",
	"phases.",
	"Illustrating",
	"the",
	"power",
	"of",
	"our",
	"approach,",
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	"generation",
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	"phosphide",
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	"the",
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	"superior",
	"in",
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	"and",
	"oxygen",
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	"reactivity",
	"over",
	"the",
	"previous",
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	"and",
	"is",
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	"water",
	"electrolysis",
	"at",
	"a",
	"current",
	"density",
	"of",
	"10",
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	"cm<sup>-2</sup>",
	"with",
	"1.5",
	"V",
	"applied",
	"bias",
	"in",
	"1",
	"M",
	"KOH",
	"electrolyte",
	"solution.",
	"</p>",
	"<p>"
	],
	"tags": [
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	]
	}
	]
	```

	### Dataset Fields

	The dataset has the following fields (also called "features"):

	```json
	{
	"tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
	"tags": "Sequence(feature=ClassLabel(names=['CATALYST', 'CO-CATALYST', 'O', 'Other', 'PROPERTY_NAME', 'PROPERTY_VALUE'], id=None), length=-1, id=None)"
	}
	```

	### Dataset Splits

	This dataset is split into a train and validation split. The split sizes are as follow:

	\| Split name \| Num samples \|
	\| ------------ \| ------------------- \|
	\| train \| 166 \|
	\| valid \| 44 \|